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<table width="100%" summary="page for ipo"><tr><td>ipo</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Initial Public Offering Data</h2>

<h3>Description</h3>

<p> Data on the relationship between the number of initial public
offerings (of shares in a company) and other potentially important variables.
It is probably necessary to lag some of the explanatory variables.
</p>


<h3>Usage</h3>

<pre>
data(ipo)
</pre>


<h3>Format</h3>

<p>A data frame with 6 columns and 156 rows. The columns are:
</p>

<dl>
<dt>n.ipo</dt><dd><p>number of initial pubilc offerings each month.</p>
</dd>
<dt>ir</dt><dd><p>the average initial return (volume weighted): this is the percentage
difference between the offer proce of shares and the price after the first day
of trading.</p>
</dd>
<dt>dp</dt><dd><p>the average percentage difference between middle of the price range
proposed at first filing of the IPO, and the eventual offer price.</p>
</dd>
<dt>reg.t</dt><dd><p>the average time between filing and offer.</p>
</dd>
<dt>t</dt><dd><p>time, in months.</p>
</dd>
<dt>month</dt><dd><p>month of the year (1 = January).</p>
</dd>
</dl>


<h3>Source</h3>

 
<p><a href="http://schwert.ssb.rochester.edu">http://schwert.ssb.rochester.edu</a>
</p>


<h3>References</h3>

<p>Lowry, M. and G.W. Schwert (2002) IPO market cycles: Bubbles or sequential
learning? The Journal of Finance 67(3), 1171-1198
</p>
<p>Wood, S.N. (2006, 2017) Generalized Additive Models: An Introduction with R. CRC
</p>


<h3>Examples</h3>

<pre>
  data(ipo)
  pairs(ipo)
</pre>


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